Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add joelbrilliant/agentic-delivery-skills --skill agentic-engineeringgit clone --depth 1 https://github.com/joelbrilliant/agentic-delivery-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/joelbrilliant/agentic-delivery-skills/agentic-engineering)<a href="https://agentmods.dev/skills/joelbrilliant/agentic-delivery-skills/agentic-engineering"><img src="https://agentmods.dev/badge/skills/joelbrilliant/agentic-delivery-skills/agentic-engineering/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/joelbrilliant/agentic-delivery-skills/agentic-engineering"><img src="https://agentmods.dev/badge/skills/joelbrilliant/agentic-delivery-skills/agentic-engineering.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00072 | $0.00681 |
| Opus 5 | $0.00036 | $0.00341 |
| Sonnet 5 | $0.00014 | $0.00136 |
| Haiku 4.5 | $0.00007 | $0.00068 |
Grade A, and why
agentic-engineering scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 95 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agentic Engineering
Use this skill to turn vague engineering work into a safe, reviewable slice.
Default flow
1. Clarify only if needed
- If the task is obvious and reversible, act.
- If scope, behaviour, owner, interface, or acceptance criteria are unclear, ask one decision-driving question at a time.
- Include your recommended answer with each question.
- If the answer can be found by reading code or docs, do that instead of asking.
- Do not use clarification as a way to avoid simple work.
2. Shape the work
Convert the agreed direction into a concise requirement.
For each slice, capture:
- owner;
- target behaviour;
- likely files or surfaces;
- acceptance criteria;
- blockers;
- human-signoff status;
- required evidence.
Prefer vertical slices with user-visible behaviour. Avoid horizontal plumbing unless it is the smallest safe step.
3. Respect the lane
Use explicit roles:
- orchestrator writes the brief and judges final evidence;
- designer/spec agent explores options only when design is in scope;
- builder implements the approved slice;
- reviewer reviews adversarially;
- final judge signs off against brief, evidence, and review outcome.
Do not let multiple agents co-build the same slice unless the write sets are independent and explicitly split.
4. Design interfaces before uncertain implementation
For uncertain APIs, modules, or UI surfaces:
- ask for divergent options first;
- prefer simple public interfaces with deep internal implementation;
- avoid abstractions that hide lack of understanding;
- state tradeoffs before building.
5. Use TDD tracer bullets where risk warrants it
- Write one behaviour test through a public interface.
- Implement the minimum to go green.
- Repeat one behaviour at a time.
- Refactor only while green.
- Avoid private-method tests and mock-heavy tests that lock implementation details.
6. Turn QA into durable briefs
Capture:
- what happened;
- expected behaviour;
- reproduction steps;
- evidence;
- severity;
- candidate files or functions.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 95 lines · 72 tokens per session scan A 86ecaba918ea
agentic-engineering is a skill published in the GitHub repository joelbrilliant/agentic-delivery-skills (2 stars, last pushed 3mo ago), licensed MIT. It adds 72 tokens to every session and 681 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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